SUMMARY Current PD measures are largely limited to the clinic and based on episodic, rater-dependent, categorical scales. The result is that the clinical trials, even early stage ones, require large sample sizes, long durations, and high costs. Moreover, these measures are prone to generating false signals of efficacy in phase 2 trials that are not found in phase 3 and likely generate missed signals of efficacy that are never detected. In the 21st century new tools are available that can generate objective, frequent, sensitive assessments of PD in real-world settings. These super computing devices, or smartphones, are increasingly ubiquitous and powerful. In March 2015, Apple released ResearchKit, an open-source platform for creating smartphone research studies. At the same time, five smartphone research studies, including one for PD (mPower), were also launched. In seven months, over 70,000 individuals across the country enrolled in these studies. Through the P20 and related efforts, we have demonstrated that assessments of voice, gait, balance, and bradykinesia conducted on the smartphone can differentiate individuals with PD from those without, correlate with traditional PD assessments, detect response to levodopa, and can be quantified in a novel mobile PD score that correlates with the MDS-UPDRS but can be administered by almost anyone anywhere anytime. In Research Project 3, we will evaluate the next generation smartphone research application (mPower 2.0) against current gold standard clinical measures of PD, assess its ability to generate novel assessments of socialization based on passively collected data, refine the mobile PD score, and improve the replicability and reproducibility of the score using advanced signal processing algorithms and neural networks In just two years after their large scale introduction, pharmaceutical companies and academic investigators are already incorporating these devices into their clinical trials. This Research Project will help accelerate these efforts to use smartphones to generate objective, passive and active, frequent real-world assessments of motor and non-motor function in PD.